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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 236756, 8 pages
Research Article

An Efficient Approximation Algorithm for Aircraft Arrival Sequencing and Scheduling Problem

1School of Economics and Management, Tongji University, Shanghai 200092, China
2Foshan Shuyuan Science and Technology Company Limited, Foshan, Guangdong 528200, China

Received 23 June 2014; Accepted 20 August 2014; Published 31 December 2014

Academic Editor: Chunlin Chen

Copyright © 2014 Weimin Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. Federal Aviation Administration, 2009,
  2. D. Böhme, “Improved airport surface traffic management by planning,” in Advanced Technologies for Air Traffic Flow Management, H. Winter and H.-G. Nüßer, Eds., vol. 198 of Lecture Notes in Control and Information Sciences, pp. 191–224, Springer, Berlin, Germany, 1994. View at Publisher · View at Google Scholar
  3. K. D. Arkind, “Requirements for a novel terminal area capacity enhancement concept in 2022,” in American Institute of Aeronautics and Astronautics, Guidance, Navigation and Control Conference Exhibit, American Institute of Aeronautics and Astronautics, Reston, Va, USA, 2004.
  4. H. R. Idris, B. Delcaire, I. Anagnostakis et al., “Identification of flow constraint and control points in depa rture operations at airport systems,” in Proceedings of the American Institute of Aeronautics and Ast ronautics, Guidance, Navigation and Control Conference, American Institute of Aero nautics and Astronautics, Boston, Mass, USA, 1998, AIAA-1998-42 91.
  5. J. E. Beasley, M. Krishnamoorthy, Y. M. Sharaiha, and D. Abramson, “Scheduling aircraft landings—the static case,” Transportation Science, vol. 34, no. 2, pp. 180–197, 2000. View at Publisher · View at Google Scholar · View at Scopus
  6. L. Bianco, P. Dell'Olmo, and S. Giordani, “Scheduling models and algorithms for TMA traffic management,” in Modelling and Simulation in Air Traffic Management, L. Bianco, P. Dell'Olmo, and A. R. Odoni, Eds., pp. 139–167, Springer, New York, NY, USA, 1997. View at Google Scholar
  7. M. R. Garey and D. S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, W. H. Freeman, New York, NY, USA, 1979. View at MathSciNet
  8. A. T. Ernst, M. Krishnamoorthy, and R. H. Storer, “Heuristic and exact algorithms for scheduling aircraft landings,” Networks, vol. 34, no. 3, pp. 229–241, 1999. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  9. G. Bencheikh, J. Boukachour, A. E. H. Alaoui, and F. E. Khoukhi, “Hybrid method for aircraft landing scheduling based on a job shop formulation,” International Journal of Computer Science and Network Security, vol. 9, pp. 78–88, 2009. View at Google Scholar
  10. M. C. Randall, “Scheduling aircraft landings using ant colony optimi sation,” in Proceedings of the IASTED International Conference on Artificial Intelligence and Soft Computing, Banff, Canada, 2002.
  11. C. R. Brinton, “An implicit enumeration algorithm for arrival air craft scheduling,” in Proceedings of the IEEE/AIAA 11th Digital Avionics Systems Conference, Seattle, Wash, USA, 1992.
  12. J. Abela, D. Abramson, M. Krishnamoorthy, A. de Silva, and G. Mills, “Computing optimal schedules for landing aircraft,” in Proceedings of the 12th National Conference of the Australian Society for Operations Research, pp. 71–90, Adelaide, Australia, 1993.
  13. J. A. Bennell, M. Mesgarpour, and C. N. Potts, “Airport runway scheduling,” 4OR, vol. 9, no. 2, pp. 115–138, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  14. Z.-H. Zhan, J. Zhang, Y. Li et al., “An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem,” IEEE Transactions on Intelligent Transportation Systems, vol. 11, no. 2, pp. 399–412, 2010. View at Publisher · View at Google Scholar · View at Scopus
  15. M. Dorigo, Optimization, learning and natural algorithms [Ph.D. thesis], Elettronica e Informazi One, Politecnico di Milano, Milano, Italy, 1992.
  16. M. Dorigo and L. M. Gambardella, “Ant colonies for the travelling salesman problem,” BioSystems, vol. 43, no. 2, pp. 73–81, 1997. View at Publisher · View at Google Scholar · View at Scopus
  17. M. Dorigo and L. M. Gambardella, “Ant colony system: a cooperative learning approach to the traveling salesman problem,” IEEE Transactions on Evolutionary Computation, vol. 1, no. 1, pp. 53–66, 1997. View at Publisher · View at Google Scholar · View at Scopus
  18. G. Bencheikh, J. Boukachour, and A. E. H. Alaoui, “Improved ant colony algorithm to solve the aircraft landing problem,” International Journal of Computer Theory and Engineering, vol. 3, pp. 224–233, 2011. View at Google Scholar
  19. H. Balakrishnan and B. G. Chandran, “Algorithms for scheduling runway operations under constrained position shifting,” Operations Research, vol. 58, no. 6, pp. 1650–1665, 2010. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  20. F. Neuman and H. Erzberger, “Analysis of delay reducing and fuel sav ing sequencing and spacing algor ithms for arrival spacing,” NASA Technical Report A-91203; NAS 1.15:10 3880; NASA-TM-103880, NASA Technical Reports Server, 1991. View at Google Scholar
  21. T. R. Willemain, H. Fan, and H. Ma, “Statistical analysis of intervals between projected airport arrivals,” DSES Technical Report 38-04-510, Rensselaer Polytechnic Institute, Troy, NY, USA, 2004. View at Google Scholar
  22. H. Lee, Tradeoff evaluation of scheduling algorithms for terminal-area air traffic control [M.S. thesis], Massachusetts Institute of Technology, Cambridge, Mass, USA, 2008.